Classic auto-correlation techniques are applied in order to detect symbols and/or other meaningful information in a corresponding data stream. Auto-correlation is performed between a presently received wireless signal and a delayed (sampled) version of that signal stored in memory. Generally, such auto-correlation techniques typically either exploit the redundancy of the orthogonal frequency-division multiplexing access (OFDMA) signal the stems from the presence of a cyclic prefix guard interval, exploit the ⅓ (one-third) symbol periodicity of the preamble of such a signal. As one example, WiMAX 802.16e signals utilize the one-third symbol periodicity mentioned above.
However, two problems are known to exist under classical auto-correlation strategies. In the first case, it is sometimes difficult or impossible to distinguish a downlink signal (or symbol thereof) that is followed by time shifted uplink signal. This is due, at least in part, to the “global” normalization of energy that is applied in the classic technique. In the second case, the periodicity of a preamble symbol within an acquired signal can make it difficult, at best, to distinguish from other symbols or portions of symbols within the signal. Classical auto-correlation can exacerbate this problem by substantially boosting all symbols within the signal to similar magnitudes, such that distinguishing the preamble (and thus, establishing a symbol-recognition synchronization) is challenging or requires multiple attempts.